CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method

by Firas M. Tuaimah, Huda M. Abdul Abass
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 1
Year of Publication: 2014
Authors: Firas M. Tuaimah, Huda M. Abdul Abass
10.5120/17492-8011

Firas M. Tuaimah, Huda M. Abdul Abass . Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method. International Journal of Computer Applications. 100, 1 ( August 2014), 41-45. DOI=10.5120/17492-8011

@article{ 10.5120/17492-8011,
author = { Firas M. Tuaimah, Huda M. Abdul Abass },
title = { Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 1 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number1/17492-8011/ },
doi = { 10.5120/17492-8011 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:28:49.879497+05:30
%A Firas M. Tuaimah
%A Huda M. Abdul Abass
%T Short-Term Electrical Load Forecasting for Iraqi Power System based on Multiple Linear Regression Method
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 1
%P 41-45
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper an investigation for the short term (up to 24 hours) load forecasting of the demand for the Iraqi Power System would be presented, using a Multiple Linear Regression (MLR) method. After a brief analytical discussion of the technique, the usage of mathematical models and the steps to compose the MLR model will be explained. As a case study, historical data consisting of hourly load demand, humidity, wind speed and temperatures of Iraqi electrical system will be used, to forecast the short term load. Two models will be presented; one for winter and the second for summer season. Algorithms implementing this forecasting technique have been programmed using MATLAB and applied to the case study. This study uses the linear static parameter estimation technique as they apply to the twenty four hour off-line forecasting problem.

References
  1. J. P. Rothe, A. K. Wadhwani and S. Wadhwani, "Short Term Load Forecasting Using Multi Parameter Regression", International Journal of Computer Science and Information Security (IJCSIS), Vol. 6, No. 2, 2009.
  2. S. A. Soliman, and A. M. Al-Kandari, "Electrical Load Forecasting: Modeling and Model Construction", pp. 82-93, 2010.
  3. S. A. Soliman, S. Persaud, K. El-Nagar and M. E. El-Hawary, "Application of Least Absolute Value Parameter Estimation Technique Based on Linear Programming to Short-Term Load Forecasting", IEEE, pp. 529-533, 1996.
  4. Hesham K. Alfares and Mohammad Nazeeruddin, "Electric load forecasting: literature survey and classication of methods", International Journal of Systems Science, volume 33, No. 1, PP. 23±34, 2002.
  5. Nahid-Al-Masood, Mehdi Z. Sadi, Shohana Rahman Deeba and Radwanul H. Siddique, "Temperature Sensitivity Forecasting of Electrical Load", The 4th International Power Engineering and Optimization Conf. (PEOCO), PP. 23-24, MALAYSIA, June 2010.
  6. Nazih Abu-Shikhah, Fawwaz Elkarmi and Osama M. Aloquili, " Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression ", Smart Grid and Renewable Energy, PP. 126-135, Vol. 2, 2011.
  7. J. P. Rothe, A. K. Wadhwani and A. K. Wadhwani, "Hybrid and Integrated Approach to Short Term Load Forecasting", International Journal of Engineering Science and Technology Vol. 2(12), PP. 7127-7132, 2010.
  8. M. Babita Jain, Manoj Kumar Nigam and Prem Chand Tiwari, "A Parameter based New Approach for Short Term Load Forecasting using Curve-fitting and Regression line method", International Journal of Engineering Research & Technology (IJERT) Vol. 1, August – 2012.
  9. N. Amral, C. S. Özveren and D King, "Short Term Load Forecasting using Multiple Linear Regression", University of Abertay Dundee, UK 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Short Term Load forecasting (STLF) Multiple Linear Regression (MLR) Weather parameters.

Powered by PhDFocusTM